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<h2>Description</h2>
<p class="Body">Adaptive supersampling is different from ordinary supersampling 
  in the sense that samples are choosen adaptively. It is a recursive method that 
  collects more samples at areas with rapid transitions.</p>
<p class="Body">The advantage with this method that makes it more attractive than 
  ordinary supersampling is that we can perform supersampling only at areas where 
  it is needed. However, the recursion itself may cause overhead, so there is 
  a trade-off between the cost of the associated nested sampling method and the 
  cost of the adaptive recursion.</p>
<p id="hidden">[See Also]</p>
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